Seaborn is one of the go-to tools for statistical data visualization in python. It has been actively developed since 2012 and in July 2018, the author released version 0.9. This version of Seaborn has several new plotting features, API changes and documentation updates which combine to enhance an already great library. This article will walk through a few of the highlights and show how to use the new scatter and line plot functions for quickly creating very useful visualizations of data.
Data visualization is the visual presentation of data or information. The goal of data visualization is to communicate data or information clearly and effectively to readers. Typically, data is visualized in the form of a chart, infographic, diagram or map.
Fbref is a popular football stats/metrics site which collections information from Ted Knutson's StatsBomb. You can save this data in a csv or excel format. This is a Python module which collects any raw csv file from Fbref and plot the data based on whichever two axes you want it to. You can also scrape data from whichever Fbref page you wish to.
Implementation of Decision Tree Classifier, Esemble Learning, Association Rule Mining and Clustering models(Kmodes & Kprototypes) for Customer attrition analysis of telecommunication company to identify the cause and conditions of the churn.
This repository contains the collection of Python and Javascript (Observable Notebook) projects made for the DTU Data Science course 02806: Social Data Analysis and Visualizations
This project understands how the student's performance (test scores) is affected by other variables such as Gender, Ethnicity, Parental level of education, Lunch and Test preparation course